This application generally relates to artificial intelligence and/or pattern recognition systems, and in particular, estimating the performance of a classifier system.
Classifier systems may be used in the field of artificial intelligence and/or pattern recognition to identify an object and then to classify it into one or more predetermined categories. One exemplary classifier system is an automated target recognition (ATR) system. For example, ATR systems are known which are used to identify and categorize military targets. Classifier systems may also be used for face recognition, agriculture classification, medical applications (e.g., detecting healthy and unhealthy tissue or cells), and many other applications.
A confusion matrix is a tool that may be used to characterize the performance of a given classifier system. Typically, the confusion matrix is generated by evaluating the response of a classifier system to known data.
However, there is no effective way to estimate the performance of classifier systems when presented with unknown data.